The central point of contention between cognitive economists and neoclassical economists hinges upon the word “rational”: Are humans rational? What do we mean by “rational”?

Neoclassicists are very keen to insist that they think humans are rational, and often characterize the cognitivist view as saying that humans are irrational. (Daniel Ariely has a habit of feeding this view, titling books things like Predictably Irrationaland The Upside of Irrationality.) But I really don’t think this is the right way to characterize the difference.

Daniel Kahneman has a somewhat better formulation (from Thinking, Fast and Slow): “I often cringe when my work is credited as demonstrating that human choices are irrational, when in fact our research only shows that Humans are not well described by the rational-agent model.” (Yes, he capitalizes the word “Humans” throughout, which is annoying; but in general it is a great book.)

The problem is that saying “humans are irrational” has the connotation of a universal statement; it seems to be saying that everything we do, all the time, is always and everywhere utterly irrational. And this of course could hardly be further from the truth; we would not have even survived in the savannah, let alone invented the Internet, if we were that irrational. If we simply lurched about randomly without any concept of goals or response to information in the environment, we would have starved to death millions of years ago.

But at the same time, the neoclassical definition of “rational” obviously does not describe human beings. We aren’t infinite identical psychopaths. Particularly bizarre (and frustrating) is the continued insistence that rationality entails selfishness; apparently economists are getting all their philosophy from Ayn Rand (who barely even qualifies as such), rather than the greats such as Immanuel Kant and John Stuart Mill or even the best contemporary philosophers such as Thomas Pogge and John Rawls. All of these latter would be baffled by the notion that selfless compassion is irrational.

Indeed, Kant argued that rationality implies altruism, that a truly coherent worldview requires assent to universal principles that are morally binding on yourself and every other rational being in the universe. (I am not entirely sure he is correct on this point, and in any case it is clear to me that neither you nor I are anywhere near advanced enough beings to seriously attempt such a worldview. Where neoclassicists envision infinite identical psychopaths, Kant envisions infinite identical altruists. In reality we are finite diverse tribalists.)

But even if you drop selfishness, the requirements of perfect information and expected utility maximization are still far too strong to apply to real human beings. If that’s your standard for rationality, then indeed humans—like all beings in the real world—are irrational.

The confusion, I think, comes from the huge gap between ideal rationality and total irrationality. Our behavior is neither perfectly optimal nor hopelessly random, but somewhere in between.

In fact, we are much closer to the side of perfect rationality! Our brains are limited, so they operate according to heuristics: simplified, approximate rules that are correct most of the time. Clever experiments—or complex environments very different from how we evolved—can cause those heuristics to fail, but we must not forget that the reason we have them is that they work extremely well in most cases in the environment in which we evolved. We are about 90% rational—but woe betide that other 10%.

The most obvious example is phobias: Why are people all over the world afraid of snakes, spiders, falling, and drowning? Because those used to be leading causes of death. In the African savannah 200,000 years ago, you weren’t going to be hit by a car, shot with a rifle bullet or poisoned by carbon monoxide. (You’d probably die of malaria, actually; for that one, instead of evolving to be afraid of mosquitoes we evolved a biological defense mechanism—sickle-cell red blood cells.) Death in general was actually much more likely then, particularly for children.

A similar case can be made for other heuristics we use: We are tribal because the proper functioning of our 100-person tribe used to be the most important factor in our survival. We are racist because people physically different from us were usually part of rival tribes and hence potential enemies. We hoard resources even when our technology allows abundance, because a million years ago no such abundance was possible and every meal might be our last.

When asked how common something is, we don’t calculate a posterior probability based upon Bayesian inference—that’s hard. Instead we try to think of examples—that’s easy. That’s the availability heuristic. And if we didn’t have mass media constantly giving us examples of rare events we wouldn’t otherwise have known about, the availability heuristic would actually be quite accurate. Right now, people think of terrorism as common (even though it’s astoundingly rare) because it’s always all over the news; but if you imagine living in an ancient tribe—or even an medieval village!—anything you heard about that often would almost certainly be something actually worth worrying about. Our level of panic over Ebola is totally disproportionate; but in the 14th century that same level of panic about the Black Death would be entirely justified.

When we want to know whether something is a member of a category, again we don’t try to calculate the actual probability; instead we think about how well it seems to fit a model we have of the paradigmatic example of that category—the representativeness heuristic. You see a Black man on a street corner in New York City at night; how likely is it that he will mug you? Pretty small actually, because there were less than 200,000 crimes in all of New York City last year in a city of 8,000,000 people—meaning the probability any given person committed a crime in the previous year was only 2.5%; the probability on any given day would then be less than 0.01%. Maybe having those attributes raises the probability somewhat, but you can still be about 99% sure that this guy isn’t going to mug you tonight. But since he seemed representative of the category in your mind “criminals”, your mind didn’t bother asking how many criminals there are in the first place—an effect called base rate neglect. Even 200 years ago—let alone 1 million—you didn’t have these sorts of reliable statistics, so what else would you use? You basically had no choice but to assess based upon representative traits.

As you probably know, people have trouble dealing with big numbers, and this is a problem in our modern economy where we actually need to keep track of millions or billions or even trillions of dollars moving around. And really I shouldn’t say it that way, because $1 million ($1,000,000) is an amount of money an upper-middle class person could have in a retirement fund, while $1 billion ($1,000,000,000) would make you in the top 1000 richest people in the world, and $1 trillion ($1,000,000,000,000) is enough to end world hunger for at least the next 15 years (it would only take about $1.5 trillion to do it forever, by paying only the interest on the endowment). It’s important to keep this in mind, because otherwise the natural tendency of the human mind is to say “big number” and ignore these enormous differences—it’s called scope neglect. But how often do you really deal with numbers that big? In ancient times, never. Even in the 21st century, not very often. You’ll probably never have $1 billion, and even $1 million is a stretch—so it seems a bit odd to say that you’re irrational if you can’t tell the difference. I guess technically you are, but it’s an error that is unlikely to come up in your daily life.

Where it does come up, of course, is when we’re talking about national or global economic policy. Voters in the United States today have a level of power that for 99.99% of human existence no ordinary person has had. 2 million years ago you may have had a vote in your tribe, but your tribe was only 100 people. 2,000 years ago you may have had a vote in your village, but your village was only 1,000 people. Now you have a vote on the policies of a nation of 300 million people, and more than that really: As goes America, so goes the world. Our economic, cultural, and military hegemony is so total that decisions made by the United States reverberate through the entire human population. We have choices to make about war, trade, and ecology on a far larger scale than our ancestors could have imagined. As a result, the heuristics that served us well millennia ago are now beginning to cause serious problems.

[As an aside: This is why the “Downs Paradox” is so silly. If you’re calculating the marginal utility of your vote purely in terms of its effect on you—you are a psychopath—then yes, it would be irrational for you to vote. And really, by all means: psychopaths, feel free not to vote. But the effect of your vote is much larger than that; in a nation of N people, the decision will potentially affect N people. Your vote contributes 1/N to a decision that affects N people, making the marginal utility of your vote equal to N*1/N = 1. It’s constant. It doesn’t matter how big the nation is, the value of your vote will be exactly the same. The fact that your vote has a small impact on the decision is exactly balanced by the fact that the decision, once made, will have such a large effect on the world. Indeed, since larger nations also influence other nations, the marginal effect of your vote is probably larger in large elections, which means that people are being entirely rational when they go to greater lengths to elect the President of the United States (58% turnout) rather than the Wayne County Commission (18% turnout).]

So that’s the problem. That’s why we have economic crises, why climate change is getting so bad, why we haven’t ended world hunger. It’s not that we’re complete idiots bumbling around with no idea what we’re doing. We simply aren’t optimized for the new environment that has been recently thrust upon us. We are forced to deal with complex problems unlike anything our brains evolved to handle. The truly amazing part is actually that we can solve these problems at all; most lifeforms on Earth simply aren’t mentally flexible enough to do that. Humans found a really neat trick (actually in a formal evolutionary sense a goodtrick, which we know because it also evolved in cephalopods): Our brains have high plasticity, meaning they are capable of adapting themselves to their environment in real-time. Unfortunately this process is difficult and costly; it’s much easier to fall back on our old heuristics. We ask ourselves: Why spend 10 times the effort to make it work 99% of the time when you can make it work 90% of the time so much easier?

Why? Because it’s so incredibly important that we get these things right.

One single asymmetry underlies millions of problems and challenges the world has always faced. No, it’s not Christianity versus Islam (or atheism). No, it’s not the enormous disparities in wealth between the rich and the poor, though you’re getting warmer.

It is the asymmetry of information—the fundamental fact that what you know and what I know are not the same. If this seems so obvious as to be unworthy of comment, maybe you should tell that to the generations of economists who have assumed perfect information in all of their models.

It’s not clear that information asymmetry could ever go away—even in the utopian post-scarcity economy of the Culture, one of the few sacred rules is the sanctity of individual thought. The closest to an information-symmetric world I can think of is the Borg, and with that in mind we may ask whether we want such a thing after all. It could even be argued that total information symmetry is logically impossible, because once you make two individuals know and believe exactly the same things, you don’t have two individuals anymore, you just have one. (And then where do we draw the line? It’s that damn Ship of Theseus again—except of course the problem was never the ship, but defining the boundaries of Theseus himself.)

Right now you may be thinking: So what? Why is asymmetric information so important? Well, as I mentioned in an earlier post, the Myerson-Satterthwaithe Theorem proves—mathematically proves, as certain as 2+2=4—that in the presence of asymmetric information, there is no market mechanism that guarantees Pareto-efficiency.

You can’t square that circle; because information is asymmetric, there’s just no way to make a free market that insures Pareto efficiency. This result is so strong that it actually makes you begin to wonder if we should just give up on economics entirely! If there’s no way we can possibly make a market that works, why bother at all?

But this is not the appropriate response. First of all, Pareto-efficiency is overrated; there are plenty of bad systems that are Pareto-efficient, and even some good systems that aren’t quite Pareto-efficient.

More importantly, even if there is no perfect market system, there clearly are better and worse market systems. Life is better here in the US than it is in Venezuela. Life in Sweden is arguably a bit better still (though not in every dimension). Life in Zambia and North Korea is absolutely horrific. Clearly there are better and worse ways to run a society, and the market system is a big part of that. The quality—and sometimes quantity—of life of billions of people can be made better or worse by the decisions we make in managing our economic system. Asymmetric information cannot be conquered, but it can be tamed.

This is actually a major subject for cognitive economics: How can we devise systems of regulation that minimize the damage done by asymmetric information? Akerlof’s Nobel was for his work on this subject, especially his famous paper “The Market for Lemons” in which he showed how product quality regulations could increase efficiency using the example of lemon cars. What he showed was, in short, that libertarian deregulation is stupid; removing regulations on product safety and quality doesn’t increase efficiency, it reduces it. (This is of course only true if the regulations are good ones; but despite protests from the supplement industry I really don’t see how “this bottle of pills must contain what it claims to contain” is an illegitimate regulation.)

Unfortunately, the way we currently write regulations leaves much to be desired: Basically, lobbyists pay hundreds of staffers to make hundreds of pages that no human being can be expected to read, and then hands them to Congress with a wink and a reminder of last year’s campaign contributions, who passes them without question. (Can you believe the US is one of the least corrupt governments in the world? Yup, that’s how bad it is out there.) As a result, we have a huge morass of regulations that nobody really understands, and there is a whole “industry” of people whose job it is to decode those regulations and use them to the advantage of whoever is paying them—lawyers. The amount of deadweight loss introduced into our economy is almost incalculable; if I had to guess, I’d have to put it somewhere in the trillions of dollars per year. At the very least, I can tell you that the $200 billion per year spent by corporations on litigation is all deadweight loss due to bad regulation. That is an industry that should not exist—I cannot stress this enough. We’ve become so accustomed to the idea that regulations are this complicated that people have to be paid six-figure salaries to understand them that we never stopped to think whether this made any sense. The US Constitution was originally printed on 6 pages.

The tax code should contain one formula for setting tax brackets with one or two parameters to adjust to circumstances, and then a list of maybe two dozen goods with special excise taxes for their externalities (like gasoline and tobacco). In reality it is over 70,000 pages.

Laws should be written with a clear and general intent, and then any weird cases can be resolved in court—because there will always be cases you couldn’t anticipate. Shakespeare was onto something when he wrote, “First, kill all the lawyers.” (I wouldn’t kill them; I’d fire them and make them find a job doing something genuinely useful, like engineering or management.)

All told, I think you could run an entire country with less than 100 pages of regulations. Furthermore, these should be 100 pages that are taught to every high school student, because after all, we’re supposed to be following them. How are we supposed to follow them if we don’t even know them? There’s a principle called ignorantia non excusat—ignorance does not excuse—which is frankly Kafkaesque. If you can be arrested for breaking a law you didn’t even know existed, in what sense can we call this a free society? (People make up strawman counterexamples: “Gee, officer, I didn’t know it was illegal to murder people!” But all you need is a standard of reasonable knowledge and due diligence, which courts already use to make decisions.)

So, in that sense, I absolutely favor deregulation. But my reasons are totally different from libertarians: I don’t want regulations to stop constraining businesses, I want regulations to be so simple and clear that no one can get around them. In the system I envision, you wouldn’t be able to sell fraudulent derivatives, because on page 3 it would clearly say that fraud is illegal and punishable in proportion to the amount of money involved.

But until that happens—and let’s face it, it’s gonna be awhile—we’re stuck with these ridiculous regulations, and that introduces a whole new type of asymmetric information. This is the way that regulations can make our economy less efficient; they distort what we can do not just by making it illegal, but by making it so we don’t know what is illegal.

The wealthy and powerful can hire people to explain—or evade—the regulations, while the rest of us are forced to live with them. You’ve felt this in a small way if you’ve ever gotten a parking ticket and didn’t know why. Asymmetric information strikes again.

I already briefly mentioned the concept in an earlier post, but Pareto-efficiency is so fundamental to both ethics and economics I decided I would spent some more time on explaining exactly what it’s about.

This is the core idea: A system is Pareto-efficient if you can’t make anyone better off without also making someone else worse off. It is Pareto-inefficient if the opposite is true, and you could improve someone’s situation without hurting anyone else.

Improving someone’s situation without harming anyone else is called a Pareto-improvement. A system is Pareto-efficient if and only if there are no possible Pareto-improvements.

Zero-sum games are always Pareto-efficient. If the game is about how we distribute the same $10 between two people, any dollar I get is a dollar you don’t get, so no matter what we do, we can’t make either of us better off without harming the other. You may have ideas about what the fair or right solution is—and I’ll get back to that shortly—but all possible distributions are Pareto-efficient.

Where Pareto-efficiency gets interesting is in nonzero-sum games. The most famous and most important such game is the so-called Prisoner’s Dilemma; I don’t like the standard story to set up the game, so I’m going to give you my own. Two corporations, Alphacomp and Betatech, make PCs. The computers they make are of basically the same quality and neither is a big brand name, so very few customers are going to choose on anything except price. Combining labor, materials, equipment and so on, each PC costs each company $300 to manufacture a new PC, and most customers are willing to buy a PC as long as it’s no more than $1000. Suppose there are 1000 customers buying. Now the question is, what price do they set? They would both make the most profit if they set the price at $1000, because customers would still buy and they’d make $700 on each unit, each making $350,000. But now suppose Alphacomp sets a price at $1000; Betatech could undercut them by making the price $999 and sell twice as many PCs, making $699,000. And then Alphacomp could respond by setting the price at $998, and so on. The only stable end result if they are both selfish profit-maximizers—the Nash equilibrium—is when the price they both set is $301, meaning each company only profits $1 per PC, making $1000. Indeed, this result is what we call in economics perfect competition.This is great for consumers, but not so great for the companies.

If you focus on the most important choice, $1000 versus $999—to collude or to compete—we can set up a table of how much each company would profit by making that choice (a payoff matrix or normal form game in game theory jargon).

A: $999

A: $1000

B: $999

A:$349k

B:$349k

A:$0

B:$699k

B: $1000

A:$699k

B:$0

A:$350k

B:$350k

Obviously the choice that makes both companies best-off is for both companies to make the price $1000; that is Pareto-efficient. But it’s also Pareto-efficient for Alphacomp to choose $999 and the other one to choose $1000, because then they sell twice as many computers. We have made someone worse off—Betatech—but it’s still Pareto-efficient because we couldn’t give Betatech back what they lost without taking some of what Alphacomp gained.

There’s only one option that’s not Pareto-efficient: If both companies charge $999, they could both have made more money if they’d charged $1000 instead. The problem is, that’s not the Nash equilibrium; the stable state is the one where they set the price lower.

This means that only case that isn’t Pareto-efficient is the one that the system will naturally trend toward if both compal selfish profit-maximizers. (And while most human beings are nothing like that, most corporations actually get pretty close. They aren’t infinite, but they’re huge; they aren’t identical, but they’re very similar; and they basically are psychopaths.)

In jargon, we say the Nash equilibrium of a Prisoner’s Dilemma is Pareto-inefficient. That one sentence is basically why John Nash was such a big deal; up until that point, everyone had assumed that if everyone acted in their own self-interest, the end result would have to be Pareto-efficient; Nash proved that this isn’t true at all. Everyone acting in their own self-interest can doom us all.

It’s not hard to see why Pareto-efficiency would be a good thing: if we can make someone better off without hurting anyone else, why wouldn’t we? What’s harder for most people—and even most economists—to understand is that just because an outcome is Pareto-efficient, that doesn’t mean it’s good.

I think this is easiest to see in zero-sum games, so let’s go back to my little game of distributing the same $10. Let’s say it’s all within my power to choose—this is called the ultimatum game. If I take $9 for myself and only give you $1, is that Pareto-efficient? It sure is; for me to give you any more, I’d have to lose some for myself. But is it fair? Obviously not! The fair option is for me to go fifty-fifty, $5 and $5; and maybe you’d forgive me if I went sixty-forty, $6 and $4. But if I take $9 and only offer you $1, you know you’re getting a raw deal.

Actually as the game is often played, you have the choice the say, “Forget it; if that’s your offer, we both get nothing.” In that case the game is nonzero-sum, and the choice you’ve just taken is not Pareto-efficient! Neoclassicists are typically baffled at the fact that you would turn down that free $1, paltry as it may be; but I’m not baffled at all, and I’d probably do the same thing in your place. You’re willing to pay that $1 to punish me for being so stingy. And indeed, if you allow this punishment option, guess what? People aren’t as stingy! If you play the game without the rejection option, people typically take about $7 and give about $3 (still fairer than the $9/$1, you may notice; most people aren’t psychopaths), but if you allow it, people typically take about $6 and give about $4. Now, these are pretty small sums of money, so it’s a fair question what people might do if $100,000 were on the table and they were offered $10,000. But that doesn’t mean people aren’t willing to stand up for fairness; it just means that they’re only willing to go so far. They’ll take a $1 hit to punish someone for being unfair, but that $10,000 hit is just too much. I suppose this means most of us do what Guess Who told us: “You can sell your soul, but don’t you sell it too cheap!”

Now, let’s move on to the more complicated—and more realistic—scenario of a nonzero-sum game. In fact, let’s make the “game” a real-world situation. Suppose Congress is debating a bill that would introduce a 70% marginal income tax on the top 1% to fund a basic income. (Please, can we debate that, instead of proposing a balanced-budget amendment that would cripple US fiscal policy indefinitely and lead to a permanent depression?)

This tax would raise about 14% of GDP in revenue, or about $2.4 trillion a year (yes, really). It would then provide, for every man, woman and child in America, a $7000 per year income, no questions asked. For a family of four, that would be $28,000, which is bound to make their lives better.

But of course it would also take a lot of money from the top 1%; Mitt Romney would only make $6 million a year instead of $20 million, and Bill Gates would have to settle for $2.4 billion a year instead of $8 billion. Since it’s the whole top 1%, it would also hurt a lot of people with more moderate high incomes, like your average neurosurgeon or Paul Krugman, who each make about $500,000 year. About $100,000 of that is above the cutoff for the top 1%, so they’d each have to pay about $70,000 more than they currently do in taxes; so if they were paying $175,000 they’re now paying $245,000. Once taking home $325,000, now only $255,000. (Probably not as big a difference as you thought, right? Most people do not seem to understand how marginal tax rates work, as evinced by “Joe the Plumber” who thought that if he made $250,001 he would be taxed at the top rate on the whole amount—no, just that last $1.)

You can even suppose that it would hurt the economy as a whole, though in fact there’s no evidence of that—we had tax rates like this in the 1960s and our economy did just fine. The basic income itself would inject so much spending into the economy that we might actually see more growth. But okay, for the sake of argument let’s suppose it also drops our per-capita GDP by 5%, from $53,000 to $50,300; that really doesn’t sound so bad, and any bigger drop than that is a totally unreasonable estimate based on prejudice rather than data. For the same tax rate might have to drop the basic income a bit too, say $6600 instead of $7000.

So, this is not a Pareto-improvement; we’re making some people better off, but others worse off. In fact, the way economists usually estimate Pareto-efficiency based on so-called “economic welfare”, they really just count up the total number of dollars and divide by the number of people and call it a day; so if we lose 5% in GDP they would register this as a Pareto-loss. (Yes, that’s a ridiculous way to do it for obvious reasons—$1 to Mitt Romney isn’t worth as much as it is to you and me—but it’s still how it’s usually done.)

But does that mean that it’s a bad idea? Not at all. In fact, if you assume that the real value—the utility—of a dollar decreases exponentially with each dollar you have, this policy could almost double the total happiness in US society. If you use a logarithm instead, it’s not quite as impressive; it’s only about a 20% improvement in total happiness—in other words, “only” making as much difference to the happiness of Americans from 2014 to 2015 as the entire period of economic growth from 1900 to 2000.

If right now you’re thinking, “Wow! Why aren’t we doing that?” that’s good, because I’ve been thinking the same thing for years. And maybe if we keep talking about it enough we can get people to start voting on it and actually make it happen.

But in order to make things like that happen, we must first get past the idea that Pareto-efficiency is the only thing that matters in moral decisions. And once again, that means overcoming the standard modes of thinking in neoclassical economics.

Something strange happened to economics in about 1950. Before that, economists from Marx to Smith to Keynes were always talking about differences in utility, marginal utility of wealth, how to maximize utility. But then economists stopped being comfortable talking about happiness, deciding (for reasons I still do not quite grasp) that it was “unscientific”, so they eschewed all discussion of the subject. Since we still needed to know why people choose what they do, a new framework was created revolving around “preferences”, which are a simple binary relation—you either prefer it or you don’t, you can’t like it “a lot more” or “a little more”—that is supposedly more measurable and therefore more “scientific”. But under this framework, there’s no way to say that giving a dollar to a homeless person makes a bigger difference to them than giving the same dollar to Mitt Romney, because a “bigger difference” is something you’ve defined out of existence. All you can say is that each would prefer to receive the dollar, and that both Mitt Romney and the homeless person would, given the choice, prefer to be Mitt Romney. While both of these things are true, it does seem to be kind of missing the point, doesn’t it?

There are stirrings of returning to actual talk about measuring actual (“cardinal”) utility, but still preferences (so-called “ordinal utility”) are the dominant framework. And in this framework, there’s really only one way to evaluate a situation as good or bad, and that’s Pareto-efficiency.

Actually, that’s not quite right; John Rawls cleverly came up with a way around this problem, by using the idea of “maximin”—maximize the minimum. Since each would prefer to be Romney, given the chance, we can say that the homeless person is worse off than Mitt Romney, and therefore say that it’s better to make the homeless person better off. We can’t say how much better, but at least we can say that it’s better, because we’re raising the floor instead of the ceiling. This is certainly a dramatic improvement, and on these grounds alone you can argue for the basic income—your floor is now explicitly set at the $6600 per year of the basic income.

But is that really all we can say? Think about how you make your own decisions; do you only speak in terms of strict preferences? I like Coke more than Pepsi; I like massages better than being stabbed. If preference theory is right, then there is no greater distance in the latter case than the former, because this whole notion of “distance” is unscientific. I guess we could expand the preference over groups of goods (baskets as they are generally called),and say that I prefer the set “drink Pepsi and get a massage” to the set “drink Coke and get stabbed”, which is certainly true. But do we really want to have to define that for every single possible combination of things that might happen to me? Suppose there are 1000 things that could happen to me at any given time, which is surely conservative. In that case there are 2^1000 = 10^300 possible combinations. If I were really just reading off a table of unrelated preference relations, there wouldn’t be room in my brain—or my planet—to store it, nor enough time in the history of the universe to read it. Even imposing rational constraints like transitivity doesn’t shrink the set anywhere near small enough—at best maybe now it’s 10^20, well done; now I theoretically could make one decision every billion years or so. At some point doesn’t it become a lot more parsimonious—dare I say, more scientific—to think that I am using some more organized measure than that? It certainly feels like I am; even if couldn’t exactly quantify it, I can definitely say that some differences in my happiness are large and others are small. The mild annoyance of drinking Pepsi instead of Coke will melt away in the massage, but no amount of Coke deliciousness is going to overcome the agony of being stabbed.

And indeed if you give people surveys and ask them how much they like things or how strongly they feel about things, they have no problem giving you answers out of 5 stars or on a scale from 1 to 10. Very few survey participants ever write in the comments box: “I was unable to take this survey because cardinal utility does not exist and I can only express binary preferences.” A few do write 1s and 10s on everything, but even those are fairly rare. This “cardinal utility” that supposedly doesn’t exist is the entire basis of the scoring system on Netflix and Amazon. In fact, if you use cardinal utility in voting, it is mathematically provable that you have the best possible voting system, which may have something to do with why Netflix and Amazon like it. (That’s another big “Why aren’t we doing this already?”)

If you can actually measure utility in this way, then there’s really not much reason to worry about Pareto-efficiency. If you just maximize utility, you’ll automatically get a Pareto-efficient result; but the converse is not true because there are plenty of Pareto-efficient scenarios that don’t maximize utility. Thinking back to our ultimatum game, all options are Pareto-efficient, but you can actually prove that the $5/$5 choice is the utility-maximizing one, if the two players have the same amount of wealth to start with. (Admittedly for those small amounts there isn’t much difference; but that’s also not too surprising, since $5 isn’t going to change anybody’s life.) And if they don’t—suppose I’m rich and you’re poor and we play the game—well, maybe I should give you more, precisely because we both know you need it more.

Perhaps even more significant, you can move from a Pareto-inefficient scenario to a Pareto-efficient one and make things worse in terms of utility. The scenario in which the top 1% are as wealthy as they can possibly be and the rest of us live on scraps may in fact be Pareto-efficient; but that doesn’t mean any of us should be interested in moving toward it (though sadly, we kind of are). If you’re only measuring in terms of Pareto-efficiency, your attempts at improvement can actually make things worse. It’s not that the concept is totally wrong; Pareto-efficiency is, other things equal, good; but other things are never equal.

So that’s Pareto-efficiency—and why you really shouldn’t care about it that much.